Recently I wanted to generate hilbert curve indexing of 2D array as a part of one experiment. The experiment wasn't very successful itself, but I found the resulting Python code for curve generation prety neat to post it.

Here are a couple of interesting references on space-filling curve construction ...

This notebook shows how Geodesic Discance Transform (GDT) using Fast Sweeping Method (FSM) can be implemented using Python. GDT can be thought of as a computation of shortest pathes on an image plane with a given cost function. It can be used as a part of more complex image processing ...

This notebook shows how ROF and TV-L1 variational denoising models can be implemented using Primal-Dual optimization alghorithm. While the denoising results may be inferior comparing to some other methods, it is still a nice toy example, showing how convex variational methods can be appied to image processing problems.

Once I happened to have both MS Kinect and PS3 Move on my table. I connected both of them to my PC (trivial for Kinect and ugly for Move). Then I tried to calibrate both cameras to match their coordinate frames. Here is the result I managed to get:

Before I learned about computer vision my main interests where computer graphics and computational modeling of physical and biological systems. At the time I was playing with voxel graphics I wanted to find a source of interesting, complex and natural-looking geometry. My adviser pointed me to the work Roeland Merks ...
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In a year 2007 I was doing a small course project on cellular
automaton simulation of physical phenomena. I was intrigued by the
simplicity of Lattice-Gas model and its ability to capture the complex
stuff that happens in fluid flows: